Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-05 19:40 UTC

CharithManaujayaMUTEC / AutoMR-Framework

AutoMR-Framework

PythonNo license detected★ 0 stars⑂ 0 forkssince May 2026View on GitHub ↗
KindLibraryhow this is determined

CharithManaujayaMUTEC/AutoMR-Framework holds a health index of 28 out of 100, placing it in the At Risk band. It scores highest on Sustainability & Governance (57/100) and lowest on Security (1/100). It was last updated 2 days ago. A single contributor accounts for most of its recent work.

28
overall / 100
At Risk

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

28
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 34 is calibrated to 28 on the published index scale (record calibration 2026-08-02).

Ownership

G.C.M. PereraPersonal account
4 followers25 public repossince Dec 2021

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIautomr1.2.0585363 days agometamorphic-testingmachine-learningdeep-learningartificial-intelligenceai-testingmodel-validationrobustness-testingautonomous-drivingcomputer-visionregressionimage-processingsoftware-testingparallel-computinghigh-performance-computingbatch-inferenceprediction-cachingepsilon-sensitivityparameter-range-testingfailure-analysisplugin-architecturetransformation-registrymetamorphic-relationsreliability-testingverificationvalidation

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

42Weak · 21% of overall

Development activity

70Good
How it's scored
36/36Push recency — last push 2 days ago
9/36Commit cadence — 13/52 weeks with commits
18/18Commit volume — 342 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year342
human_commit_share1
days_since_last_push2
active_weeks_last_year13

Release discipline

1Critical
How it's scored
0/27Ships releases — no releases published
0/36Release recency — no releases
0/27Release cadence — no releases
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count0

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

21At Risk · 17% of overall

Popularity & adoption

1Critical
How it's scored
0/60Stars — 0 stars
0/25Forks — 0 forks
0/15Watchers — 0 watchers
Inputs used
forks0
stars0
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

25At Risk
How it's scored
22.5/22.5README
0/22.5License — no license file detected
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseno
readme_badges8
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateno

Ecosystem adoption (downloads)

46Weak
How it's scored
36.9/80Monthly downloads — 585 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesautomr
dependents—
ecosystemspypi
total_downloads—
monthly_downloads585
unverified_packages_excluded—
Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

57Moderate · 23% of overall

Maintainer resilience (bus factor)

14Critical
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0.8/22.5Commit distribution — top contributor authored 96% of commits
2.7/13.5Contributor breadth — 2 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor1
contributors_sampled2
top_contributor_share0.965

Issue & PR responsiveness

88Excellent
How it's scored
0/42Issue resolution — no issues or no data
25/30PR acceptance — 5/6 decided PRs merged
13/13Newcomer PR acceptance — 1/1 first-time contributors' PRs merged in 30d
0/15OpenSSF Scorecard: Code-Review — no data
Inputs used
merged_prs5
open_issues0
closed_issues0
prs_merged_7d1
prs_decided_7d1
prs_merged_30d1
prs_decided_30d1
issue_closed_ratio—
closed_unmerged_prs1
first_time_authors_30d1
first_time_prs_merged_30d1
first_time_prs_decided_30d1
Excluded from scoring (no data or not applicable): Issue resolution. Remaining weights renormalized.

Ownership & stewardship

43Weak
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
5/25Owner reach — 4 followers of CharithManaujayaMUTEC
19.7/25Track record — 25 public repos, account ~4 yr old
Inputs used
followers4
owner_typeUser
is_verified—
owner_loginCharithManaujayaMUTEC
public_repos25
account_age_days1,711
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 3 days ago
20/20Version history — 36 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesautomr
ecosystemspypi
any_deprecatedno
min_days_since_publish3

Engineering Quality

Are baseline engineering and documentation practices in place?

37Weak · 19% of overall

Engineering practices

1Critical
How it's scored
0/24CI workflows
0/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_cino
has_testsno
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://github.com/CharithManaujayaMUTEC/AutoMR-Framework/wiki
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics—
has_wikiyes
homepage—
docs_sitehttps://github.com/CharithManaujayaMUTEC/AutoMR-Framework/wiki
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

1Critical · 16% of overall

Security posture

1Critical
How it's scored
0/30Security policy (SECURITY.md)
0/25Dependabot config
0/25Dependency lockfiles — published library — lockfiles are an application concern, not expected
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles—
manifestspyproject.toml, requirements.txt
has_codeql_workflowno
has_security_policyno
has_dependabot_configno
Excluded from scoring (no data or not applicable): Dependency lockfiles. Remaining weights renormalized.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

24At Risk · 4% of overall

Agent context & guidance

1Critical
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0.5/40Legible commit history — 1 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.01
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

1Critical
How it's scored
0/18One-command bootstrap
0/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practice — no agent-authored commits among the last 100
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsno
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configno
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/120 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes52,235
source_files_sampled120
oversized_source_files0

Machine-readable interfaces

100Exceptional
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — examples
Inputs used
example_dirsexamples
has_mcp_signalno
api_schema_files—
interfaces_expected_of—
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

0GitHub stars
2contributors
342commits, last 12 months
2days since last push
0releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
  • OpenSSF Scorecard did not return a usable result (killed by SIGKILL — most likely the container's memory limit); skipping Scorecard checks

More detail

Direct dependencies 31
RegistryPackageVersion constraintManifest
PyPInumpy>=1.26.4,<2.0pyproject.toml
PyPIpandas>=2.2.2pyproject.toml
PyPIscipy>=1.13.1pyproject.toml
PyPIopencv-python>=4.10.0pyproject.toml
PyPIPillow>=10.4.0pyproject.toml
PyPIscikit-image>=0.24.0pyproject.toml
PyPIimageio>=2.37.0pyproject.toml
PyPImatplotlib>=3.9.0pyproject.toml
PyPIseaborn>=0.13.2pyproject.toml
PyPItensorflow>=2.19.0pyproject.toml
PyPItensorboard>=2.19.0pyproject.toml
PyPItorch>=2.7.0pyproject.toml
PyPItorchvision>=0.22.0pyproject.toml
PyPIscikit-learn>=1.5.0pyproject.toml
PyPIxgboost>=2.1.0pyproject.toml
PyPIonnx>=1.18.0pyproject.toml
PyPIonnxruntime>=1.22.0pyproject.toml
PyPIkornia>=0.7.3pyproject.toml
PyPInoise>=1.2.2pyproject.toml
PyPItqdm>=4.67.1pyproject.toml
PyPIrequests>=2.32.3pyproject.toml
PyPIpython-dotenv>=1.0.1pyproject.toml
PyPIPyYAML>=6.0.2pyproject.toml
PyPItyping-extensions>=4.12.2pyproject.toml
PyPIaddict>=2.4.0pyproject.toml
PyPIpathspec>=0.12.1pyproject.toml
PyPIpackaging>=24.2pyproject.toml
PyPIpsutil>=6.1.1pyproject.toml
PyPIjoblib>=1.4.2pyproject.toml
PyPInetworkx>=3.4.2pyproject.toml
PyPIpsutil>=5.9.0pyproject.toml
All dependencies not collected

The resolved dependency set could not be collected for this report: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

Raw JSON report machine-readable

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Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.